NutrientDynamics

citation: Shelby E. McIlroy, Casey P. terHorst, Mark Teece, Mary Alice Coffroth (2022) Nutrient dynamics in coral symbiosis depend on both the relative and absolute abundance of Symbiodiniaceae species. Microbiome

Load Libraries

library(dplyr)
library(ggplot2)
library(interflex)
library(wesanderson)
library(car)
library(knitr)

Import data minor formats

Filter File (FilterData.csv) and Stable Isotope Data by Filter (IsotopesByFilter.csv)

polyp_data<-read.csv("RecruitsByFilter.csv",header = T)
realdata<-read.csv(file="IsotopesByFilter.csv",header = T)
realdata$Filter<-as.character(realdata$Filter)

Symbiont density and composition across recruits

Spearman’s test to check for a correlation between the density of symbionts within a recruit and the ratio of symbiont species

SpT<-cor.test(polyp_data$NumTotal,polyp_data$PercentB, method="spearman",exact=FALSE)
SpT

## 
##  Spearman's rank correlation rho
## 
## data:  polyp_data$NumTotal and polyp_data$PercentB
## S = 33234011, p-value = 0.8266
## alternative hypothesis: true rho is not equal to 0
## sample estimates:
##         rho 
## 0.009071257

Table of symbiont density and symbiont composition across filters subsequently used in SIA analyses

Filter	avgTotal	avgB	minTotal	minB	maxTotal	maxB
101	487224.5	1.0000000	92165.5	1.0000000	1222620.0	1.0000000
105	745045.8	0.9986744	157997.0	0.9880699	1516039.0	1.0000000
106	994115.5	0.9901316	704630.5	0.9838100	1904399.0	0.9971492
107	1077985.3	0.9769939	508046.0	0.9723363	1712819.5	0.9836851
109	701177.4	0.9484360	179028.5	0.9416801	1528243.5	0.9563802
110	677881.8	0.9143466	116889.5	0.8821341	1770324.5	0.9416457
111	538037.5	0.8679713	143825.5	0.8479790	1175128.5	0.8795435
112	567355.9	0.8215042	75103.0	0.8029045	1164044.0	0.8381623
113	298929.0	0.7374998	83944.0	0.6979079	595896.0	0.7856916
114	417237.7	0.5673313	58180.5	0.5438711	1490926.5	0.5986435
115	268738.8	0.4945384	117092.5	0.4635342	494116.0	0.5277840
116	851287.5	0.4223467	95949.0	0.4011089	2036947.5	0.4484514
117	439236.0	0.3831510	58383.5	0.3771028	1182860.0	0.3967924
118	755547.8	0.3462678	56423.5	0.3191870	1632288.0	0.3685297
119	804276.7	0.2981005	352247.0	0.2843354	1858412.5	0.3121944
120	668280.6	0.2659583	233198.0	0.2569290	1051529.5	0.2779034
121	712029.5	0.2347079	229376.0	0.2229417	1616965.0	0.2533138
122	528216.5	0.2039470	200879.0	0.1854782	788245.5	0.2200231
123	528653.7	0.1726026	315518.0	0.1661478	796103.0	0.1809802
124	752131.1	0.1601849	290538.5	0.1527942	1294198.5	0.1660982
125	771905.1	0.1481103	262741.5	0.1399914	1529563.0	0.1524782
126	773595.6	0.1344502	265891.5	0.1294345	1552390.0	0.1390628
127	852532.8	0.1195182	330407.0	0.1143290	2227235.5	0.1275739
128	1020178.2	0.1071333	401170.0	0.1013785	1740970.0	0.1136545
129	894086.9	0.0899172	487476.5	0.0844588	1339292.5	0.0962398
130	851089.1	0.0791006	532322.0	0.0750516	1391533.5	0.0843178
131	1023938.7	0.0658829	296257.5	0.0608532	1747147.5	0.0728520
132	776287.4	0.0560944	347214.0	0.0501511	1071973.0	0.0592773
133	1015835.8	0.0450492	243859.0	0.0425270	1588195.0	0.0488792
134	1047744.9	0.0375665	482989.5	0.0312645	1729549.5	0.0423864
135	934440.5	0.0264688	95791.5	0.0212649	1597494.5	0.0308356
136	886615.1	0.0157772	443345.0	0.0121576	1243228.0	0.0200135
137	924399.0	0.0087392	336542.5	0.0054598	1753832.5	0.0117583
138	1172438.8	0.0031178	477368.5	0.0011359	2209858.0	0.0052659
139	723727.7	0.0000000	459567.5	0.0000000	1311611.0	0.0000000
141	351451.8	0.0000000	102000.5	0.0000000	1120392.0	0.0000000
143	771572.6	0.0000000	215859.0	0.0000000	1687294.0	0.0000000
144	490419.3	0.0000000	76195.0	0.0000000	1137185.0	0.0000000
145	839800.5	0.0000000	302904.0	0.0000000	1665926.5	0.0000000
146	764848.3	0.0000000	421809.5	0.0000000	1483902.0	0.0000000
147	443710.8	0.0000000	239568.0	0.0000000	728672.0	0.0000000
148	470368.2	0.0000000	197141.0	0.0000000	637689.5	0.0000000
149	495601.0	0.0000000	143643.5	0.0000000	991280.5	0.0000000
151	592994.5	0.0000000	224616.0	0.0000000	1324708.0	0.0000000
156	580757.1	0.0000000	296912.0	0.0000000	919621.5	0.0000000
158	581435.1	0.0000000	235147.5	0.0000000	944510.0	0.0000000
160	972407.4	0.0000000	141067.5	0.0000000	1681603.0	0.0000000

Fig. 2. Recruit combinations for SIA

To obtain enough mass, separated host or symbiont tissues from 8-10 recruits were combined onto a glass fibre filter prior to stable isotope analysis. Variation in the (A) relative ratio of symbionts (S. microadriaticum : B. minutum) and (B) symbiont density (cells/recruit) for the combined recruits are shown for each filter along the x-axis. The mean (points) and range (bars) of data are shown. Combinations were based on similarity in the relative ratio of symbionts as measured by qPCR; host and symbiont tissue combinations were maintained to generate host and symbiont filter pairs.

ggplot(byfilter)+
  geom_pointrange(aes(x=Filter,y=avgTotal,ymin=minTotal,ymax=maxTotal,color=avgB))+
  theme_bw()+
  theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank(),
        panel.background = element_blank(), axis.line = element_line(colour = "black"),
        axis.text.x=element_blank())+
  scale_color_gradientn(colours=rev(wes_palette("Zissou1")),name="Symbiont Ratio (%B.m.)")+
  scale_y_continuous(labels = scales::comma)+
  xlab("Filter")+
  ylab("Symbiont density (cells/recruit)")

ggplot(byfilter)+
  geom_pointrange(aes(x=Filter,y=avgB,ymin=minB,ymax=maxB,color=avgTotal))+
  theme_bw()+
  theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank(),
        panel.background = element_blank(), axis.line = element_line(colour = "black"),
        axis.text.x=element_blank())+
  scale_color_gradientn(colours=c("#D8B70A", "#02401B"), labels = scales::comma,name="Symbiont density")+
  scale_y_continuous(labels = scales::comma)+
  xlab("Filter")+
  ylab("Symbiont Ratio (Prop of B.m.)")

Stable Isotope Analysis

AP¹³C in Host Tissues

Multiple linear regression of AP¹³C(host) ~ symbiont density X symbiont ratio

lmHostAPC<-lm(HostAP_C~PercentB+CellsPerPolyp,data=realdata)
summary(lmHostAPC)

## 
## Call:
## lm(formula = HostAP_C ~ PercentB + CellsPerPolyp, data = realdata)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -0.04147 -0.01043  0.00030  0.01252  0.03573 
## 
## Coefficients:
##                Estimate Std. Error t value Pr(>|t|)    
## (Intercept)   1.188e+00  9.022e-03 131.660  < 2e-16 ***
## PercentB      5.429e-04  7.486e-05   7.252 4.31e-09 ***
## CellsPerPolyp 2.697e-08  1.128e-08   2.391   0.0211 *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.01848 on 45 degrees of freedom
## Multiple R-squared:  0.5598, Adjusted R-squared:  0.5403 
## F-statistic: 28.61 on 2 and 45 DF,  p-value: 9.59e-09

res<-resid(lmHostAPC)
qqnorm(res)
qqline(res)

layout(matrix(c(1,2,3,4),2,2)) # optional 4 graphs/page 
plot(lmHostAPC)

Fig. 3ab. Atom percent ¹³C values for host tissues based on symbiont ratios (the relative ratio of S. microadriaticum and B. minutum symbionts, top) and symbiont densities (total cells per recruit, bottom).

Solid black lines show significant relationships as determined by generalized linear models. In the case of an interactive effect, the primary response is divided into levels of the secondary response variable, then modeled and plotted independently for each level with non-significant (triangles and dashed lines) and significant (circles and solid line) effects.

ggplot(realdata,aes(x=PercentB,y=HostAP_C,color=CellsPerPolyp))+
  geom_point(size=2.5)+
  theme_bw()+
  theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank(),
        panel.background = element_blank(), axis.line = element_line(colour = "black"))+
   geom_smooth(method="lm", colour="black", se = F)+
   scale_color_gradientn(colours=c("#D8B70A", "#02401B"), labels = scales::comma,name="Symbiont density")+
  xlab("Symbiont Ratio (Percent B.m.)")+
  ylab("AP 13C in Host Tissue")

ggplot(realdata,aes(x=CellsPerPolyp,y=HostAP_C,color=PercentB))+
  geom_point(size=2.5)+
  theme_bw()+
  theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank(),
        panel.background = element_blank(), axis.line = element_line(colour = "black"))+
  coord_cartesian(clip = "off") +
   geom_smooth(method="lm", colour="black", se = F)+
  scale_color_gradientn(colours=rev(wes_palette("Zissou1")),name="Symbiont Ratio (% B.m.)")+
  scale_x_continuous(labels = scales::comma)+
  xlab("Symbiont density (cells/recruit)")+
  ylab("AP 13C in Host Tissue")

AP¹³C in Symbiont Tissues

Multiple linear regression of AP¹³C(sym) ~ symbiont density X symbiont ratio

lmSymAPC<-lm(SymAP_C~PercentB*CellsPerPolyp,data=realdata)
summary(lmSymAPC)

## 
## Call:
## lm(formula = SymAP_C ~ PercentB * CellsPerPolyp, data = realdata)
## 
## Residuals:
##       Min        1Q    Median        3Q       Max 
## -0.057488 -0.024180 -0.007259  0.020156  0.115629 
## 
## Coefficients:
##                          Estimate Std. Error t value Pr(>|t|)    
## (Intercept)             1.292e+00  2.375e-02  54.390   <2e-16 ***
## PercentB               -4.821e-04  4.291e-04  -1.124   0.2673    
## CellsPerPolyp          -4.430e-08  3.033e-08  -1.460   0.1513    
## PercentB:CellsPerPolyp  1.141e-09  5.254e-10   2.172   0.0353 *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.03464 on 44 degrees of freedom
## Multiple R-squared:  0.2252, Adjusted R-squared:  0.1724 
## F-statistic: 4.263 on 3 and 44 DF,  p-value: 0.009976

res<-resid(lmSymAPC)
qqnorm(res)
qqline(res)

layout(matrix(c(1,2,3,4),2,2)) # optional 4 graphs/page 
plot(lmSymAPC)

##examine the effects of outlier removal
realdata1<-filter(realdata,Filter!="145")
realdata1<-filter(realdata1,Filter!="144")
lmSymAPC1<-lm(SymAP_C~PercentB*CellsPerPolyp,data=realdata1)
summary(lmSymAPC1)

## 
## Call:
## lm(formula = SymAP_C ~ PercentB * CellsPerPolyp, data = realdata1)
## 
## Residuals:
##       Min        1Q    Median        3Q       Max 
## -0.051763 -0.015627 -0.003833  0.019258  0.060035 
## 
## Coefficients:
##                          Estimate Std. Error t value Pr(>|t|)    
## (Intercept)             1.273e+00  1.826e-02  69.711   <2e-16 ***
## PercentB               -2.103e-04  3.243e-04  -0.649    0.520    
## CellsPerPolyp          -2.985e-08  2.312e-08  -1.291    0.204    
## PercentB:CellsPerPolyp  9.327e-10  3.951e-10   2.361    0.023 *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.02561 on 42 degrees of freedom
## Multiple R-squared:  0.4132, Adjusted R-squared:  0.3713 
## F-statistic: 9.858 on 3 and 42 DF,  p-value: 4.8e-05

Marginal Effects Plot to visualize significant density x ratio interaction term on AP¹³C in symbiont tissues

Fig.S2.

The significant interaction effect of symbiont ratio and symbiont density on atom percent ¹³C values of symbiont tissues was examined by plotting the marginal effect of symbiont ratio (S.m.:B.m.) as moderated by symbiont density (cells/recruit).

interflex(estimator = "linear",data = realdata , Y = "SymAP_C", D = "PercentB", X= "CellsPerPolyp",xlab = "Moderator: Symbiont density (cells/recruit)",ylab = "Marginal Effect of Symbiont Ratio on AP13Csym",theme.bw = TRUE,show.grid = FALSE,cex.axis = 0.7, cex.lab=0.7)

#subset data according to marginal effects plots to visualize trends
More7<-filter(realdata,CellsPerPolyp>=700000)
notMore7<-filter(realdata,CellsPerPolyp<700000)

Fig. 3cd. Atom percent ¹³C values for symbiont tissues based on symbiont ratios (the relative ratio of S. microadriaticum and B. minutum symbionts) and symbiont densities (total cells per recruits).

Solid black lines show significant relationships as determined by generalized linear models. In the case of an interactive effect, the primary response is divided into levels of the secondary response variable, then modeled and plotted independently for each level with non-significant (triangles and dashed lines) and significant (circles and solid line) effects.

ggplot(More7,aes(x=PercentB,y=SymAP_C,color=CellsPerPolyp))+
    geom_point(size=2.5)+ 
  theme_bw()+
  theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank(),
        panel.background = element_blank(), axis.line = element_line(colour = "black"),
        axis.text.x=element_blank())+
  geom_smooth(method="lm", colour="black", se = F)+
  geom_point(data=notMore7,size=2.5,shape=17)+
  geom_smooth(data=notMore7,method="lm",color="gray",linetype="dashed", se =F)+
  scale_color_gradientn(colours=c("#D8B70A", "#02401B"),name="Symbiont density")+
  xlab("Percent B.m.")+
  ylab("AP 13C in Symbiont Tissues")

ggplot(realdata,aes(x=CellsPerPolyp,y=SymAP_C,color=PercentB))+
  geom_point(size=2.5)+
  theme_bw()+
  theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank(),
        panel.background = element_blank(), axis.line = element_line(colour = "black"))+
  scale_color_gradientn(colours=rev(wes_palette("Zissou1")),name="Symbiont Ratio (% B.m.)")+
  scale_x_continuous(labels = scales::comma)+
  xlab("Symbiont density (cells/recruit)")+
  ylab("AP 13C in Symbiont Tissue")

AP¹⁵N in Host Tissues

Multiple linear regression of AP¹⁵N(host) ~ symbiont density X symbiont ratio

lmHostAPN<-lm(HostAP_N~PercentB*CellsPerPolyp,data=realdata)
summary(lmHostAPN)

## 
## Call:
## lm(formula = HostAP_N ~ PercentB * CellsPerPolyp, data = realdata)
## 
## Residuals:
##       Min        1Q    Median        3Q       Max 
## -0.022750 -0.009800 -0.000628  0.009734  0.046457 
## 
## Coefficients:
##                          Estimate Std. Error t value Pr(>|t|)    
## (Intercept)             4.338e-01  1.007e-02  43.099  < 2e-16 ***
## PercentB               -3.591e-04  1.804e-04  -1.991  0.05290 .  
## CellsPerPolyp          -4.005e-08  1.284e-08  -3.119  0.00324 ** 
## PercentB:CellsPerPolyp  4.609e-10  2.204e-10   2.091  0.04249 *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.0145 on 43 degrees of freedom
##   (1 observation deleted due to missingness)
## Multiple R-squared:  0.1846, Adjusted R-squared:  0.1278 
## F-statistic: 3.246 on 3 and 43 DF,  p-value: 0.03097

res<-resid(lmHostAPN)
qqnorm(res)
qqline(res)

layout(matrix(c(1,2,3,4),2,2)) # optional 4 graphs/page 
plot(lmHostAPN)

Marginal Effects Plot to visualize significant density x ratio interaction term on AP¹⁵N in host tissues

Fig. S3.

The significant interaction effect of symbiont ratio and symbiont density on atom percent ¹⁵N values of host tissues was examined by plotting the marginal effect of symbiont density as moderated by symbiont ratio (S.m.:B.m.).

interflex(estimator = "linear",data = realdata , Y = "HostAP_N", X = "PercentB", D= "CellsPerPolyp",treat.type = "continuous",nbins=7,xlab = "Moderator: Symbiont Ratio",ylab = "Marginal Effect of Sym Density on AP15Nhost",na.rm=T,theme.bw = TRUE,show.grid = FALSE,cex.axis = 0.7, cex.lab=0.7)

less_B50<-filter(realdata,PercentB<=50)
more_B50<-filter(realdata,PercentB>50)

**Fig. 4. Atom percent ¹⁵N values for host tissues based on symbiont ratios (the relative ratio of S.m. and B.m. symbionts) and symbiont densities (total cells per recruit).**

Solid black lines show significant relationships as determined by generalized linear models. In the case of an interactive effect, the primary response is divided into levels of the secondary response variable, then modeled and plotted independently for levels of non-significant (triangles and dashed lines) and significant (circles and solid line) effects.

ggplot(realdata,aes(x=PercentB,y=HostAP_N,color=CellsPerPolyp))+
  geom_point(size=2.5)+
  theme_bw()+
  theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank(),
        panel.background = element_blank(), axis.line = element_line(colour = "black"))+
  scale_color_gradientn(colours=c("#D8B70A", "#02401B"), labels = scales::comma,name="Symbiont density")+
  xlab("Symbiont Ratio (Percent B.m.)")+
  ylab("AP 15N in Host Tissue")

ggplot(less_B50,aes(x=CellsPerPolyp,y=HostAP_N,color=PercentB))+
  geom_point(size=2.5)+
  theme_bw()+
  theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank(),
        panel.background = element_blank(), axis.line = element_line(colour = "black"))+
  geom_smooth(method="lm", se = F,color="black")+
  geom_point(data=more_B50,shape=17,size=2.5)+
  geom_smooth(data=more_B50, method = "lm", se = F, color="gray",linetype="dashed")+
  scale_color_gradientn(colours=rev(wes_palette("Zissou1")),name="Symbiont Ratio (% B.m.)")+
  scale_x_continuous(labels = scales::comma)+
  scale_y_continuous(limits=c(0.375,0.475))+
  xlab("Symbiont density (cells/recruit)")+
  ylab("AP 15N in Host Tissues")

AP¹⁵N in Symbiont Tissues

Multiple linear regression of AP¹⁵N(sym) ~ symbiont density X symbiont ratio

lmSymAPN<-lm(SymAP_N~PercentB*CellsPerPolyp,data=realdata)
summary(lmSymAPN)

## 
## Call:
## lm(formula = SymAP_N ~ PercentB * CellsPerPolyp, data = realdata)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -0.03275 -0.01093 -0.00181  0.00742  0.06651 
## 
## Coefficients:
##                          Estimate Std. Error t value Pr(>|t|)    
## (Intercept)             4.647e-01  1.300e-02  35.757  < 2e-16 ***
## PercentB               -9.569e-04  2.348e-04  -4.075 0.000189 ***
## CellsPerPolyp          -6.692e-08  1.660e-08  -4.032 0.000216 ***
## PercentB:CellsPerPolyp  9.536e-10  2.875e-10   3.317 0.001831 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.01896 on 44 degrees of freedom
## Multiple R-squared:  0.3574, Adjusted R-squared:  0.3136 
## F-statistic: 8.158 on 3 and 44 DF,  p-value: 0.0001987

res<-resid(lmSymAPN)
qqnorm(res)
qqline(res)

layout(matrix(c(1,2,3,4),2,2)) # optional 4 graphs/page 
plot(lmSymAPN)

Marginal Effects Plot to visualize significant density x ratio interaction term on AP¹⁵N in symbiont tissues

Fig. S4.

The significant interaction effect of symbiont ratio and symbiont density on atom percent ¹⁵N values of symbiont tissues was examined by plotting the marginal effect of symbiont ratio (S.m.:B.m.) as moderated by symbiont density (cells/recruit).

Fig. S5.

The significant interaction effect of symbiont ratio and symbiont density on atom percent ¹⁵N values of symbiont tissues was examined by plotting the marginal effect of symbiont density as moderated by symbiont ratio (S.m.:B.m.).

interflex(estimator = "linear",data = realdata , Y = "SymAP_N", X = "PercentB", D= "CellsPerPolyp",treat.type = "continuous",xlab = "Moderator: Symbiont Ratio",ylab = "Marginal Effect of Sym Density on AP15Nsym",na.rm=T,theme.bw = TRUE,show.grid = FALSE,cex.axis = 0.7, cex.lab=0.7,nbins=7)

interflex(estimator = "linear",data = realdata , Y = "SymAP_N", D = "PercentB", X= "CellsPerPolyp",treat.type = "continuous",nbins=7,xlab = "Moderator: Symbiont Density",ylab = "Marginal Effect of Sym Ratio on AP15Nsym",na.rm=T,theme.bw = TRUE,show.grid = FALSE,cex.axis = 0.7, cex.lab=0.7)

#subset data according to marginal effects plots to visualize trends
More8<-filter(realdata,CellsPerPolyp>=800000)
notMore8<-filter(realdata,CellsPerPolyp<800000)

Fig. 4. Atom percent ¹⁵N values for symbiont tissues based on symbiont ratios (the relative ratio of S.m. and B.m. symbionts) and symbiont densities (total cells per recruit).

Solid black lines show significant relationships as determined by generalized linear models. In the case of an interactive effect, the primary response is divided into levels of the secondary response variable, then modeled and plotted independently for levels of non-significant (triangles and dashed lines) and significant (circles and solid line) effects.

ggplot(notMore8,aes(x=PercentB,y=SymAP_N,color=CellsPerPolyp))+
    geom_point(size=2.5)+ 
  theme_bw()+
  theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank(),
        panel.background = element_blank(), axis.line = element_line(colour = "black"),
        axis.text.x=element_blank())+
  geom_smooth(method="lm", colour="black", se = F)+
  geom_point(data=More8,size=2.5,shape=17)+
  geom_smooth(data=More8,method="lm",color="gray",linetype="dashed", se =F)+
  scale_color_gradientn(colours=c("#D8B70A", "#02401B"),name="Symbiont density")+
  xlab("Percent B.m.")+
  ylab("AP 15N in Symbiont Tissues")

ggplot(less_B50,aes(x=CellsPerPolyp,y=SymAP_N,color=PercentB))+
  geom_point(size=2.5)+
  theme_bw()+
  theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank(),
        panel.background = element_blank(), axis.line = element_line(colour = "black"))+
  geom_smooth(method="lm", se = F,color="black")+
  geom_point(data=more_B50,shape=17,size=2.5)+
  geom_smooth(data=more_B50, method = "lm", se = F, color="gray",linetype="dashed")+
  scale_color_gradientn(colours=rev(wes_palette("Zissou1")),name="Symbiont Ratio (% B.m.)")+
  scale_x_continuous(labels = scales::comma)+
  xlab("Symbiont density (cells/recruit)")+
  ylab("AP 15N in Symbiont Tissues")

Nutrient Sharing

Fig. 5. Comparison of Host and Symbiont isotopic enrichment of ¹³C and ¹⁵N.

Red and blue lines show linear fit to data of recruits dominated by either S. microadriaticum, or B. minutum respectively. Dotted line shows a 1:1 relationship.

ggplot(more_B50,aes(x=SymAP_N,y=HostAP_N,color=PercentB))+
  geom_point(size=2.5)+
  theme_bw()+
  theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank(),
        panel.background = element_blank(), axis.line = element_line(colour = "black"))+
    geom_smooth(method="glm", colour="#3b9ab2", se = F, method.args = list(family="gaussian"))+ 
  geom_point(data=less_B50,shape=17,size=2.5)+
  geom_smooth(data=less_B50,method="glm", colour="#F21A00", se = F, method.args = list(family="gaussian"))+
  geom_abline(slope=1,intercept=0,colour="gray",linetype="dashed")+
  scale_color_gradientn(colours=rev(wes_palette("Zissou1")),name=element_blank())+
  xlab("AP 15N in Sym Tissue")+
  ylab("AP 15N in Host Tissue")

Total New Nitrogen per Recruit

Multiple linear regression combined Total N(new) per recruit ~ symbiont density X symbiont ratio

lmNewN<-lm(CombNewNPolyp~PercentB*CellsPerPolyp,data=realdata)
summary(lmNewN)

## 
## Call:
## lm(formula = CombNewNPolyp ~ PercentB * CellsPerPolyp, data = realdata)
## 
## Residuals:
##        Min         1Q     Median         3Q        Max 
## -0.0114658 -0.0048160 -0.0000326  0.0029751  0.0198387 
## 
## Coefficients:
##                          Estimate Std. Error t value Pr(>|t|)    
## (Intercept)             2.707e-02  4.528e-03   5.977 3.95e-07 ***
## PercentB               -1.730e-04  8.116e-05  -2.131  0.03883 *  
## CellsPerPolyp          -1.884e-08  5.777e-09  -3.262  0.00217 ** 
## PercentB:CellsPerPolyp  2.388e-10  9.918e-11   2.408  0.02041 *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.006521 on 43 degrees of freedom
##   (1 observation deleted due to missingness)
## Multiple R-squared:  0.202,  Adjusted R-squared:  0.1464 
## F-statistic: 3.629 on 3 and 43 DF,  p-value: 0.02021

res<-resid(lmNewN)
qqnorm(res)
qqline(res)

layout(matrix(c(1,2,3,4),2,2)) # optional 4 graphs/page 
plot(lmNewN)

##examine the effects of outlier removal
realdata1<-filter(realdata,Filter!="145")
realdata1<-filter(realdata1,Filter!="144")

lmNewN1<-lm(CombNewNPolyp~PercentB*CellsPerPolyp,data=realdata1)
summary(lmNewN1)

## 
## Call:
## lm(formula = CombNewNPolyp ~ PercentB * CellsPerPolyp, data = realdata1)
## 
## Residuals:
##        Min         1Q     Median         3Q        Max 
## -0.0093720 -0.0040182  0.0003198  0.0034878  0.0114762 
## 
## Coefficients:
##                          Estimate Std. Error t value Pr(>|t|)    
## (Intercept)             2.427e-02  3.872e-03   6.267  1.8e-07 ***
## PercentB               -1.342e-04  6.808e-05  -1.971  0.05550 .  
## CellsPerPolyp          -1.684e-08  4.898e-09  -3.438  0.00136 ** 
## PercentB:CellsPerPolyp  2.111e-10  8.281e-11   2.549  0.01462 *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.005356 on 41 degrees of freedom
##   (1 observation deleted due to missingness)
## Multiple R-squared:  0.2522, Adjusted R-squared:  0.1975 
## F-statistic: 4.609 on 3 and 41 DF,  p-value: 0.007199

res<-resid(lmNewN1)
qqnorm(res)
qqline(res)
layout(matrix(c(1,2,3,4),2,2)) # optional 4 graphs/page

plot(lmNewN1)

Marginal Effects Plot to visualize significant density x ratio interaction term on Total New Nitrogen per Recruit

Fig. S6.

The significant interaction effect of symbiont ratio and symbiont density on total assimilated nitrogen (mg/recruit) was examined by plotting the marginal effect of symbiont density as moderated by symbiont ratio (S.m.:B.m.).

interflex(estimator = "linear",data = realdata , Y = "CombNewNPolyp", X = "PercentB", D= "CellsPerPolyp",treat.type = "continuous",xlab = "Moderator: Symbiont Ratio",ylab = "Marginal Effect of Sym Density on Total New N",na.rm=T,theme.bw = TRUE,show.grid = FALSE,cex.axis = 0.7, cex.lab=0.7,nbins=7)

Fig. 6. Total amount of newly assimilated nitrogen (mg) from combined host and symbiont tissues.

Solid black line shows significant relationship as determined by generalized linear models, with p-values. To visualize the significant interaction betwen symbiont density and symbiont ratio, data for symbiont ratios are plotted independently for levels of non-significant, <1:1, mostly B. minutum (triangles and dashed lines) and significant >1:1, mostly S. microadriaticum (circles and solid line) effects.

ggplot(less_B50,aes(x=CellsPerPolyp,y=CombNewNPolyp,color=PercentB))+
  geom_point(size=2.5)+
  theme_bw()+
  theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank(),
        panel.background = element_blank(), axis.line = element_line(colour = "black"))+
  geom_smooth(method="lm", se = F,color="black")+
  geom_point(data=more_B50,shape=17,size=2.5)+
  geom_smooth(data=more_B50, method = "lm", se = F, color="gray",linetype="dashed")+
  scale_color_gradientn(colours=rev(wes_palette("Zissou1")),name="Symbiont Ratio (% B.m.)")+
  scale_x_continuous(labels = scales::comma)+
  xlab("Symbiont density (cells/recruit)")+
  ylab("Total Assimilated N (mg)/recruit")

NutrientDynamics_Markdown

SEM

11/OCT/2022

citation: Shelby E. McIlroy, Casey P. terHorst, Mark Teece, Mary Alice Coffroth (2022) Nutrient dynamics in coral symbiosis depend on both the relative and absolute abundance of Symbiodiniaceae species. Microbiome

Load Libraries

Import data minor formats

Filter File (FilterData.csv) and Stable Isotope Data by Filter (IsotopesByFilter.csv)

Symbiont density and composition across recruits

Spearman’s test to check for a correlation between the density of symbionts within a recruit and the ratio of symbiont species

Table of symbiont density and symbiont composition across filters subsequently used in SIA analyses

Fig. 2. Recruit combinations for SIA

Stable Isotope Analysis

AP13C in Host Tissues

Multiple linear regression of AP13C(host) ~ symbiont density X symbiont ratio

Fig. 3ab. Atom percent 13C values for host tissues based on symbiont ratios (the relative ratio of S. microadriaticum and B. minutum symbionts, top) and symbiont densities (total cells per recruit, bottom).

AP13C in Symbiont Tissues

Multiple linear regression of AP13C(sym) ~ symbiont density X symbiont ratio

Marginal Effects Plot to visualize significant density x ratio interaction term on AP13C in symbiont tissues

Fig.S2.

The significant interaction effect of symbiont ratio and symbiont density on atom percent 13C values of symbiont tissues was examined by plotting the marginal effect of symbiont ratio (S.m.:B.m.) as moderated by symbiont density (cells/recruit).

Fig. 3cd. Atom percent 13C values for symbiont tissues based on symbiont ratios (the relative ratio of S. microadriaticum and B. minutum symbionts) and symbiont densities (total cells per recruits).

AP15N in Host Tissues

Multiple linear regression of AP15N(host) ~ symbiont density X symbiont ratio

Marginal Effects Plot to visualize significant density x ratio interaction term on AP15N in host tissues

Fig. S3.

The significant interaction effect of symbiont ratio and symbiont density on atom percent 15N values of host tissues was examined by plotting the marginal effect of symbiont density as moderated by symbiont ratio (S.m.:B.m.).

Fig. 4. Atom percent 15N values for host tissues based on symbiont ratios (the relative ratio of S.m. and B.m. symbionts) and symbiont densities (total cells per recruit).

AP15N in Symbiont Tissues

Multiple linear regression of AP15N(sym) ~ symbiont density X symbiont ratio

Marginal Effects Plot to visualize significant density x ratio interaction term on AP15N in symbiont tissues

Fig. S4.

The significant interaction effect of symbiont ratio and symbiont density on atom percent 15N values of symbiont tissues was examined by plotting the marginal effect of symbiont ratio (S.m.:B.m.) as moderated by symbiont density (cells/recruit).

Fig. S5.

The significant interaction effect of symbiont ratio and symbiont density on atom percent 15N values of symbiont tissues was examined by plotting the marginal effect of symbiont density as moderated by symbiont ratio (S.m.:B.m.).

Fig. 4. Atom percent 15N values for symbiont tissues based on symbiont ratios (the relative ratio of S.m. and B.m. symbionts) and symbiont densities (total cells per recruit).

Nutrient Sharing

Fig. 5. Comparison of Host and Symbiont isotopic enrichment of 13C and 15N.

Red and blue lines show linear fit to data of recruits dominated by either S. microadriaticum, or B. minutum respectively. Dotted line shows a 1:1 relationship.

Total New Nitrogen per Recruit

Multiple linear regression combined Total N(new) per recruit ~ symbiont density X symbiont ratio

Marginal Effects Plot to visualize significant density x ratio interaction term on Total New Nitrogen per Recruit

Fig. S6.

The significant interaction effect of symbiont ratio and symbiont density on total assimilated nitrogen (mg/recruit) was examined by plotting the marginal effect of symbiont density as moderated by symbiont ratio (S.m.:B.m.).

Fig. 6. Total amount of newly assimilated nitrogen (mg) from combined host and symbiont tissues.

END

AP¹³C in Host Tissues

Multiple linear regression of AP¹³C(host) ~ symbiont density X symbiont ratio

Fig. 3ab. Atom percent ¹³C values for host tissues based on symbiont ratios (the relative ratio of S. microadriaticum and B. minutum symbionts, top) and symbiont densities (total cells per recruit, bottom).

AP¹³C in Symbiont Tissues

Multiple linear regression of AP¹³C(sym) ~ symbiont density X symbiont ratio

Marginal Effects Plot to visualize significant density x ratio interaction term on AP¹³C in symbiont tissues

The significant interaction effect of symbiont ratio and symbiont density on atom percent ¹³C values of symbiont tissues was examined by plotting the marginal effect of symbiont ratio (S.m.:B.m.) as moderated by symbiont density (cells/recruit).

Fig. 3cd. Atom percent ¹³C values for symbiont tissues based on symbiont ratios (the relative ratio of S. microadriaticum and B. minutum symbionts) and symbiont densities (total cells per recruits).

AP¹⁵N in Host Tissues

Multiple linear regression of AP¹⁵N(host) ~ symbiont density X symbiont ratio

Marginal Effects Plot to visualize significant density x ratio interaction term on AP¹⁵N in host tissues

The significant interaction effect of symbiont ratio and symbiont density on atom percent ¹⁵N values of host tissues was examined by plotting the marginal effect of symbiont density as moderated by symbiont ratio (S.m.:B.m.).

**Fig. 4. Atom percent ¹⁵N values for host tissues based on symbiont ratios (the relative ratio of S.m. and B.m. symbionts) and symbiont densities (total cells per recruit).**

AP¹⁵N in Symbiont Tissues

Multiple linear regression of AP¹⁵N(sym) ~ symbiont density X symbiont ratio

Marginal Effects Plot to visualize significant density x ratio interaction term on AP¹⁵N in symbiont tissues

The significant interaction effect of symbiont ratio and symbiont density on atom percent ¹⁵N values of symbiont tissues was examined by plotting the marginal effect of symbiont ratio (S.m.:B.m.) as moderated by symbiont density (cells/recruit).

The significant interaction effect of symbiont ratio and symbiont density on atom percent ¹⁵N values of symbiont tissues was examined by plotting the marginal effect of symbiont density as moderated by symbiont ratio (S.m.:B.m.).

Fig. 4. Atom percent ¹⁵N values for symbiont tissues based on symbiont ratios (the relative ratio of S.m. and B.m. symbionts) and symbiont densities (total cells per recruit).

Fig. 5. Comparison of Host and Symbiont isotopic enrichment of ¹³C and ¹⁵N.